Fermentation has long been a key technology for mass production of biological products. An economically sound fermentation process usually has to demonstrate the following advantages: optimal cell production, maximum product accumulation and minimum nutrient consumption. In most industrial applications, fed-batch cultures have been found preferable over batch cultures because during a fed-batch fermentation an optical cell growth rate and nutrient consumption rate can be achieved by controlling the nutrient feeding in a desired range. A successful fed-batch culture can reach a maximum cell density of over 100 g/L cell dry weight (Mori et al., Journal of Chemical Enqineerinq of Japan 12:313-39(1979)). Thus the highest levels of volumetric productivity can be achieved. In a batch culture it is generally necessary to provide a high initial concentration of nutrients in order to sustain cell growth over an extended time. As a result, substrate inhibition may occur in the early stages of cell growth, followed by a nutrient deficiency in the late stages of fermentation. Consequently, an optimal cell growth rate and product accumulation rate can hardly be obtained in a batch culture.
A number of nutrient feeding strategies have been explored as a means of controlling cell growth in fed-batch cultures. The strategies can be divided into two groups: non-feed-back control and feed-back control. The former includes controlling the nutrient feeding rate according to a pre-determined, constant or exponential profile (Yamane et al., J.Ferment.Technol. 54:229-240(1976)). This type of feeding scheme requires that the cell performs reproducibly each time in both the inoculum and early batch culture stages to warrant the match of the feeding rate to the actual cell growth rate. This is a kind of very stringent control which may work very consistently, but could easily get off track if cell activity changes due to any environmental fluctuation. Feed-back control, on the other hand, can react based on demand and is directly correlated to the cell activities actually existing throughout the fermentation. The control parameters which have been used for feed-back controls include respiratory quotient (Wang et al., Biotechnol.Bioeng. 19:69-81(1977)); pH (Nishio et al., J.Ferment. Technol.55:151-155(1977)), (Kim et al., Biotechnol Lett. 14:811-816(1992)); or DOC (Mori et al., Journal of Chemical Encineering of Japan 12:313-39(1979)), (Yano et al., J. Ferment. Technol. 56:416-420(1978)), (Cutayar et al., Biotechnol Lett. 11:155-160(1989)).
With the advancement of recombinant DNA technology, the above fermentation technology has been further developed for production of recombinant proteins in recombinant organisms such as E.coli and many other cell cultures. A number of recombinant proteins which are produced by fermentation technology such as recombinant human insulin (Humulin.RTM., Lilly), recombinant erythropoietin (Epogen.RTM., Amgen), recombinant tissue plasminogen activator (Activase.RTM., Genentech), and recombinant interferon (Roferon.RTM., Roche), are now available for human pharmaceutical use.
Some of these successful production fermentation processes for recombinant proteins have also been published in scientific journals or patents (Fieschko et al., Chem. Eng. Commun. 45:229-240(1986)), (Riesenberg et al., Patent No. DD290215(1991)). However, most production scale fermentation processes (published or unpublished) for recombinant proteins are either a batch culture (Flodh. Acta Paediatr. Scand. 325:1-9.(1986)) or a fed-batch batch culture with a manual feed control scheme ((Fieschko et al., Chem. Eng. Commun. 45:229-240(1986)). These processes are hardly reproducible, and require labor-intensive "baby sitting" by experienced personnel. Moreover, the conditions under which the process is operated are certainly not optimized.
Most biotechnology companies do not spend time in developing an efficient fermentation process with an optimized control strategy because they frequently face short deadlines in putting their products on the market. Another reason is related to regulatory compliance. Some believe that an automated fermentation process with optimized computer controls is too complicated for validation purposes. As a result, few feed-back controlled fermentation processes have ever been developed for pharmaceutical production purposes.
More recently, it has been shown that plasmid DNA can be used as a non-viral gene delivery system for clinical applications (Wang et al., Proc. Nat'l. Acad. Sci. USA 90:4156-4160 (1993). For such applications, which include gene therapy and genetic immunization, the plasmids themselves rather than the expressed proteins are the desired pharmaceutical products. Accordingly, there is a need for pharmaceutically acceptable large scale processes for production of intact plasmid DNA. Although it is natural to think that it might be possible to produce plasmid DNA with the fermentation technology developed for recombinant proteins, the biological processes involved are fundamentally different due to different end products: plasmid DNA vs. protein. Since cells are required to produce plasmid DNA in large quantities rather than proteins, precursor pools will be different: nucleotides vs. amino acids. Secondly, plasmid production requires a different synthetic pathway than protein: DNA replication vs. transcription and translation. Thirdly, plasmid DNA is susceptible to degradation by nucleases rather than proteases. The undesired by-products of plasmid production will also be different: proteins, RNA, chromosomal DNA and other forms of DNA vs. DNA and RNA for protein products. Furthermore, in order to obtain a high yield of plasmid DNA at the end of fermentation, cell growth rate may need to be regulated because a fast (close to maximum) growth rate may result in significant plasmid loss during fermentation (Zabriskie et al. Enzyme Microb. Technol. 8:706-717(1986)). These factors may require special control strategies for fermentation of plasmid DNA. Specifically, an optimal cell growth rate and nutrient environment have to be identified and maintained to sustain a high plasmid DNA stability and-integrity.
Recombinant bacterial plasmids for pharmaceutical applications typically contain large segments of insert DNA for disease targets, as well as the expression vectors themselves which typically comprise marker genes for selection purposes, origin sequences for DNA replication in bacteria, and eukaryotic promoter and other regulatory sequences for expression in mammalian cells. Such plasmid molecules tend to be large, on the order of 10.sup.6 -10.sup.7 daltons(5-20 kb), and particularly susceptible to mutations during fermentation. Therefore, a successful plasmid fermentation process has to provide a culture environment which maximizes the conversion of energy and substrates to plasmid DNA with high stability and integrity, while minimizing other by-products such as protein, RNAs and other DNAs as much as possible.
This invention demonstrates that the above goals can be achieved through a careful medium formulation and an automated feed-back controlled nutrient feeding strategy based on DOC (dissolved oxygen concentration) and pH. The process is based on the principle that when the carbon source in the culture is about to be completely depleted, DOC will rise rapidly. This is presumably due to a slowing down of respiratory activity (i.e., oxidative reactions). If the demand for the carbon source is not met, the pH of the culture will rise too. This phenomenon is probably caused by the consumption of metabolic fatty acids (e.g., acetic acid et al.) by cells as an alternative carbon source. The increase in pH could also be caused by production of ammonium ions as a result of protein degradation. Based upon the above, we designed an automated process using both pH and DO controllers to control the nutrient feeding rates. The DO controller also controls the agitation rate and the pH controller also controls the addition of base to the fermentation medium. By adjusting DO and pH control set points, the cell specific growth rate was decreased about 10 fold. As a result, plasmid DNA yield was increased by about 10 fold.